Connecting Grounds of Discrimination to Real People's Real Experiences
Bibliographic record
Abstract
From the outset, the prevailing approach to human rights statutes in Canada has been predicated on a closed list of prohibited grounds of discrimination. The early drafts of s. 15 of the Canadian Charter of Rights and Freedoms likewise had a closed list of enumerated grounds, but the final version qualifies those grounds as "in particular", opening the door for a broader application of s. 15. Nonetheless, the Supreme Court of Canada, with the exception of Justice L'Heureux-Dube, has insisted that establishing a prohibited ground, either enumerated or analogous, is a requisite condition to a s. 15 breach. In the aftermath of Vriend, the interaction between the Charter and human rights legislation now means that the consitution can dictate the addition of further grounds of discrimination to human rights statutes. Although the grounds of discrimination have been expanding, both by legislative and constitutional intervention, grounds of discrimination remain a principal focus of anti-discrimination law, both statutory and constitutional. Is the continuing insistence on grounds appropriate, or would it be preferrable, as advocated by Justice L'Heureux-Dube, to move away from a focus on grounds? My short answer is that it would be a mistake to abandon or de-emphasize grounds. My longer answer, as explored in what follows, is that while a formalistic approach to grounds is problematic, a more "complicated" approach to grounds offers more insight than hinderance. Furthermore, the overlapping and intersection of grounds is an important part of that complication. A fuller appreciation of the significance of grounds, rather than a de-emphasis on grounds, is what is needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.095 |
| Scholarly communication | 0.021 | 0.019 |
| Open science | 0.002 | 0.025 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".